Tensor Completion

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1 papers in the last 28 days · 0.0% of indexed attention

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Period ending 2026-09-07

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27 papers

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Near-Optimal Nonconvex Matrix Completion
Sep 15, 2026Jian-Feng Cai, Xiliang Lu, Juntao YouTensor Completion Optimal Sample Complexity
Coupled Tensor-Tensor Completion Method with Applications in Drug Repurposing
Sep 2, 2026Maryam Bagherian, Albert Hung, Ivo Dinov +1Tensor Completion Drug Discovery
Robust Low-Tubal-Rank Tensor Completion under Cross-Concentrated Sampling
Aug 4, 2026HanQin Cai, Longxiu Huang, Jing Qin +1Tensor Completion Sparse Observations
Graph-Based Correlation Matrix Generation: A Convex Optimization Approach
Jul 24, 2026Ali Fakhar, K{é}vin Polisano, Ir{è}ne Gannaz +1Tensor Completion Exponential Random Graph Models
Graph-Regularized Low-Rank Matrix Completion by Variable Projection
Jul 10, 2026Benoît Loucheur, P. -A. Absil, Michel JournéeTensor Completion Low-Rank Factorization
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion
Jul 6, 2026Adam Fisch, Daniel Deutsch, Joshua Maynez +5Model Evaluation Tensor Completion
Dual-Attention Convolution Experts for Sparse Tensor Completion
Jun 19, 2026Yanlei Liu, Zhenyu LiaoTensor Completion Sparsity
Low-Rank Tensor Completion Based on Fractional Regularization with Ky Fan p-k Norm
Jun 17, 2026Shan Fan, Feng Zhang, Jianjun Wang +2Tensor Completion Low-Rank Tensor Decomposition
Robust Neural Tucker Factorization with Bias Correction and Adaptive Initialization
Jun 15, 2026Yuchao Su, Yixin RanTensor Completion Neural Tangent Kernel
Latent Structural Categorical Matrix Completion with Application to Quasispecies Analysis
Jun 6, 2026Qian Zhang, Meixia LinTensor Completion
Low-rank Distributional Matrix Completion
Jun 2, 2026Jiayi Wang, Raymond K. W. WongTensor Completion Low-Rank Factorization
Rank-Constrained Deep Matrix Completion for Group Recommendation
Jun 1, 2026Mubaraka Sani Ibrahim, Lehel Csató, Isah Charles SaiduRecommender Systems Tensor Completion
Spectra-Guided Neural Tucker Factorization
May 30, 2026Fusheng Wang, Yikai HouTensor Completion Tensor
Improved Guarantees for Heterogeneous Treatment-Effect Estimation via Matrix Completion
May 28, 2026Anay Mehrotra, Phuc Tran, Van H. Vu +1Heterogeneous Treatment Effects Tensor Completion
Open Problem: Separating Geometric and Algorithmic Compression via Cayley-Table Completion
May 28, 2026Dongsung HuhTensor Completion Optimal Sample Complexity
Group-Aware Matrix Estimation and Latent Subspace Recovery
May 19, 2026Hamza Golubovic, Matthew Shen, Genevera I. Allen +1Tensor Completion Low-Rank Factorization
Self-Supervised Learning for Sparse Matrix Reordering
May 17, 2026Ziwei Li, Tao Yuan, Fangfang Liu +3Tensor Completion Sparsity
Learning Fill-in Reduction Ordering via Graph Policy Optimization for Sparse Matrices
May 17, 2026Ziwei Li, Shuzi Niu, Huiyuan Li +2Tensor Completion Relative Policy Optimization
Sample-efficient inductive matrix completion with noise and inexact side-information
May 16, 2026Yuepeng Yang, Cong MaTensor Completion Sparse Observations
Empirical Bayes 1-bit matrix completion
May 10, 2026Takeru MatsudaTensor Completion Sparse Observations
Low Rank Tensor Completion via Adaptive ADMM
May 5, 2026Niclas Führling, Getuar Rexhepi, Giuseppe Thadeu Freitas de AbreuTensor Completion Alternating Direction Method Of Multiplier
Active multiple matrix completion with adaptive confidence sets
May 4, 2026Andrea Locatelli, Alexandra Carpentier, Michal ValkoTensor Completion Active Learning
Quaternion Nonlinear Transform-Induced Nuclear Norm for Low-Rank Tensor Completion
May 2, 2026Biswarup Karmakar, Ratikanta BeheraTensor Completion Quaternion
Inductive Convolution Nuclear Norm Minimization for Tensor Completion with Arbitrary Sampling
Apr 18, 2026Wei Li, Yuyang Li, Kaile Du +2Tensor Completion Tensor
LLM Evaluation as Tensor Completion: Low Rank Structure and Semiparametric Efficiency
Apr 7, 2026Jiachun Li, David Simchi-Levi, Will Wei SunLarge Language Model Evaluation Tensor Completion
Towards Reliable Recommender Systems for Rating Data
Dec 30, 2024Aurore Archimbaud, Andreas Alfons, Ines WilmsRecommender Systems Tensor Completion
Multiple Testing of Linear Forms for Noisy Matrix Completion
Dec 1, 2023Wanteng Ma, Lilun Du, Dong Xia +1Tensor Completion False Discovery Rate

Sep 15, 2026 · math.NAJ/K move · Enter open · S save

Near-Optimal Nonconvex Matrix Completion

Jian-Feng Cai, Xiliang Lu, Juntao You

We study nonconvex methods for matrix completion, the problem of recovering a low-rank matrix from a subset of its entries. Convex methods achieve sample complexity linear in the matrix dimension and the rank, up to logarithmic factors, whereas global guarantees for commonly used nonconvex methods require a higher polynomial dependence on the rank. We close this gap by analyzing Riemannian gradient descent (RGD) and Riemannian Gauss--Newton (RGN) methods. For an

n\times n

matrix of rank

r

with incoherence parameter

μ

and condition number

κ

, the two methods achieve exact recovery with high probability from

O(μnr\log n\log(nκ))

and

O(μnr\log n\log(2μrκ))

observations, respectively. The methods use a multiscale residual initialization, while the analysis simultaneously controls the spectral error and incoherence. The resulting RGD iterates converge linearly, whereas RGN eventually converges Q-quadratically.

Tensor Completion Optimal Sample Complexity

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